Fear conditioning has a role in anxiety-disorders and the neurobiological correlates of it are not yet well understood. Therefore, we trained a machine learning predictive model on individual functional resting state connectivity data to predict the emotional aspects of fear conditioning. The model was found to predict individual pain-related threat learning measured by the change of valence with an explained variance of 24%-41%. These results highlight the potential of machine learning to enhance our understanding of fear conditioning.
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